Women of African ancestry (AA) women are more likely than those with European ancestry (EA) to be diagnosed with breast cancer before age 45, and to have more aggressive tumors, with negative staining for estrogen and progesterone receptors and HER-2 (triple negative). They are also more likely to have basal-like breast tumors, an intrinsic breast cancer subtype with poor prognosis. The reasons for these disparities are unclear. We propose to combine samples, data and expertise from 4 of the largest studies of breast cancer in AA women to elucidate risk factors for early-onset aggressive breast cancer. The primary dependent variable in each of the 4 Projects in this P01 is breast cancer subtype, with particular emphasis on basal-like tumors. Thus, a major purpose of this Core is to coordinate collection of tumor blocks and construction of tissue microarrays (TMAs). Tumor blocks will be collected in the CBCS, BWHS and WCHS. Immunohistochemistry will be performed for identification of breast cancer subtypes, with slides read by two independent pathologists. Data on subtypes of patients in the MEC will be independently evaluated and sent to the Biostatistics and Data Management Core. Core C will conduct genotyping for all 4 Projects. The Core will coordinate DNA extraction, whole genome amplification, quantification and plating of DNAs from all 4 studies, and genotyping using 3 OPAs developed for the lllumina GoldGate platform The Core will also resequence DNA from a subset of basal-like and luminal A cases to identify novel SNPs for fine-mapping and to discover rare susceptibility alleles. To further assist with fine-mapping and to identify GWAS-related expression signatures in basal-like and luminal A tumors for Project 1, fresh frozen basal-like and luminal A breast tumors will be assayed for gene expression using the Agilent 244K microarray. Core C will also provide consultation to Project investigators in matters related to tumor pathology and genomics. The Core leaders will work with Project PIs to provide expertise in breast cancer pathology and tumor subtyping, design OPAs, perform quality control and assist with data interpretation. An on-line study database with archived digital images of stained tumor sections and genotype cluster data will facilitate timely data analysis. The consistent and rigorous handling and processing of all biospecimens will guarantee the integrity of the P01 collaboration.